AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Training

Live Online & Classroom Enterprise Certification Training

Learn to develop, train, and deploy AI/ML models using Red Hat OpenShift AI with hands-on experience.

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What is AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Certification Training about?

AI267 provides developers and data scientists with practical skills to build AI/ML applications on Red Hat OpenShift AI. The course covers data science projects, Jupyter notebooks, model training, custom notebook images, model serving, and data science pipelines, enabling participants to deploy scalable and automated machine learning workflows in OpenShift AI environments.

What are the objectives of AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Certification Training ?

Develop and deploy AI/ML applications using Red Hat OpenShift AI.
Train, enhance, and serve machine learning models effectively.
Manage users, resources, and custom notebook images.
Implement data science pipelines and automation workflows.
Apply best practices using Red Hat OpenShift AI tools and RHOAI.

Who is AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Certification Training for?

Data scientists building AI/ML applications.
Developers deploying AI/ML models on OpenShift AI.
Machine learning engineers managing model lifecycle.
IT professionals integrating AI/ML into cloud-native environments.
Teams seeking to automate ML workflows and pipelines.

What are the prerequisites for AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Certification Training?

Experience with Linux and OpenShift 4.x environments.
Basic knowledge of AI/ML concepts.
Familiarity with containerized applications.
Experience with Python programming.
Understanding of Jupyter notebooks or similar IDEs.

Available Training Modes

Live Online Training

Course Outline Expand All

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Module 1: Introduction to Red Hat OpenShift AI

Identify main features, architecture, and components of OpenShift AI.

Module 2: Data Science Projects

Organize code, configuration, workbenches, and data connections.

Module 3: Jupyter Notebooks

Execute and test code interactively in notebooks.

Module 4: Red Hat OpenShift AI Installation

Install and manage OpenShift AI components.

Module 5: User and Resource Management

Manage users and allocate resources efficiently.

Module 6: Custom Notebook Images

Create and import custom notebook images.

Module 7: Introduction to Machine Learning

Learn ML concepts, types, and workflows.

Module 8: Training Models

Train models using default and custom workbenches.

Module 9: Enhancing Model Training with RHOAI

Apply best practices in ML and data science using RHOAI.

Module 10: Introduction to Model Serving

Export, share, and serve trained ML models.

Module 11: Model Serving in Red Hat OpenShift AI

Serve trained models within OpenShift AI.

Module 12: Introduction to Data Science Pipelines

Define and set up pipelines for data science projects.

Module 13: Working with Pipelines

Create pipelines using Kubeflow SDK and Elyra.

Module 14: Controlling Pipelines and Experiments

Configure, monitor, and track pipelines with artifacts, metrics, and experiments.

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Who is the instructor for this training?

The trainer for this AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Training has extensive experience in this domain, including years of experience training & mentoring professionals.

AI267: Developing and Deploying AI/ML Applications on Red Hat OpenShift AI Certification Training - Certification & Exam

SpringPeople is the Authorized Training Partner of Red Hat.
The training cost is exclusive of Exam/Certification Fee
Please reach us at redhat@springpeople.com for more details

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